load("~/Documents/MiGASti/Databases/gene_matrix.RData")
metadata <- read.table("~/Documents/MiGASti/Databases/metadata.txt")
#set rownames to Sample
row.names(metadata) <- metadata$Sample
setwd("~/Documents/MiGASti/Databases")
exclude <- read.table("samples2remove.txt")
exclude <- exclude$x
genes_tpm_filt = genes_tpm[, !colnames(genes_tpm) %in% exclude]
#Excludes the samples from filters.
#dim(genes_tpm_filt)
metadata_filt = metadata[ !(rownames(metadata) %in% exclude), ]
length(metadata_filt)
#check for expression of markers in dataset
markers = "~/Documents/MiGASti/Databases/Markers_stim.xlsx"
markers = read_excel(markers, col_names = TRUE)
markers = as.data.frame(markers)
gencode_30 = read.table("~/Documents/MiGASti/Databases/ens.geneid.gencode.v30")
colnames(gencode_30) = c("ensembl","symbol")
genes_tpm_filt = log2((genes_tpm_filt) + 1)
genes_tpm_filt <- as.data.frame(genes_tpm_filt)
setDT(genes_tpm_filt, keep.rownames = "ensembl")
genes_tpm_filt$ensembl
res_name = merge(genes_tpm_filt, gencode_30, by="ensembl")
rownames(res_name) = res_name$ensemblmarker_expression = merge(res_name, markers, by ="symbol")
dim (marker_expression)
head (marker_expression)
metadata_filt_ordered <- metadata_filt[colnames(genes_tpm_filt),]
metadata_filt_ordered = metadata_filt_ordered[-1,]
all(rownames(metadata_filt_ordered) == colnames (genes_tpm_filt)) #TRUE
Stimulation <- metadata_filt_ordered$Stimulation#expected to be increased in LPS
IL1B <- marker_expression[13, ]
IL1B$ensembl = NULL
IL1B$symbol = NULL
IL1B_new<-as.data.frame(t(IL1B))
df = data.frame(Stimulation, IL1B_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("IL1B") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in LPS
IL6 <- marker_expression[14, ]
IL6$ensembl = NULL
IL6$symbol = NULL
IL6_new<-as.data.frame(t(IL6))
df = data.frame(Stimulation, IL6_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("IL6") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in LPS
TNF <- marker_expression[25, ]
TNF$ensembl = NULL
TNF$symbol = NULL
TNF_new<-as.data.frame(t(TNF))
df = data.frame(Stimulation, TNF_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("TNF") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in IFNy
CXCL9 <- marker_expression[9, ]
CXCL9$ensembl = NULL
CXCL9$symbol = NULL
CXCL9_new<-as.data.frame(t(CXCL9))
df = data.frame(Stimulation, CXCL9_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("CXCL9") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in IFNy
CXCL10 <- marker_expression[7, ]
CXCL10$ensembl = NULL
CXCL10$symbol = NULL
CXCL10_new<-as.data.frame(t(CXCL10))
df = data.frame(Stimulation, CXCL10_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("CXCL10") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in IFNy
CXCL11 <- marker_expression[8, ]
CXCL11$ensembl = NULL
CXCL11$symbol = NULL
CXCL11_new<-as.data.frame(t(CXCL11))
df = data.frame(Stimulation, CXCL11_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("CXCL11") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in TNF
CCL2 <- marker_expression[3, ]
CCL2$ensembl = NULL
CCL2$symbol = NULL
CCL2_new<-as.data.frame(t(CCL2))
df = data.frame(Stimulation, CCL2_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("CCL2") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in TNF
VCAM1 <- marker_expression[26, ]
VCAM1$ensembl = NULL
VCAM1$symbol = NULL
VCAM1_new<-as.data.frame(t(VCAM1))
df = data.frame(Stimulation, VCAM1_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("VCAM1") +
xlab("Stimulation") + ylab("log2((TPM)+1)")##expected to be MyD88 dependent based on Lin et al. 2017
SAA3P <- marker_expression[22, ]
SAA3P$ensembl = NULL
SAA3P$symbol = NULL
SAA3P_new<-as.data.frame(t(SAA3P))
df = data.frame(Stimulation, SAA3P_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("SAA3P") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be MyD88 dependent based on Lin et al. 2017
SLC13A3 <- marker_expression[23, ]
SLC13A3$ensembl = NULL
SLC13A3$symbol = NULL
SLC13A3_new<-as.data.frame(t(SLC13A3))
df = data.frame(Stimulation, SLC13A3_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("SLC13A3") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be MyD88 dependent based on Lin et al. 2017
CXCL1 <- marker_expression[6, ]
CXCL1$ensembl = NULL
CXCL1$symbol = NULL
CXCL1_new<-as.data.frame(t(CXCL1))
df = data.frame(Stimulation, CXCL1_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("CXCL1") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be reduced: Breen et al.Â
NR3C1 <- marker_expression[17, ]
NR3C1$ensembl = NULL
NR3C1$symbol = NULL
NR3C1_new<-as.data.frame(t(NR3C1))
df = data.frame(Stimulation, NR3C1_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("NR3C1") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be reduced: Breen et al.Â
NR3C2 <- marker_expression[18, ]
NR3C2$ensembl = NULL
NR3C2$symbol = NULL
NR3C2_new<-as.data.frame(t(NR3C2))
df = data.frame(Stimulation, NR3C2_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("NR3C2") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in Dex
#expected to be increased in Dex/Il4
CD163 <- marker_expression[4, ]
CD163$ensembl = NULL
CD163$symbol = NULL
CD163_new<-as.data.frame(t(CD163))
df = data.frame(Stimulation, CD163_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("CD163") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in dex/il4
CD206 <- marker_expression[16, ]
CD206$ensembl = NULL
CD206$symbol = NULL
CD206_new<-as.data.frame(t(CD206))
df = data.frame(Stimulation, CD206_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("CD206") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in IL4 based on Li et al. 2018
IL10 <- marker_expression[12, ]
IL10$ensembl = NULL
IL10$symbol = NULL
IL10_new<-as.data.frame(t(IL10))
df = data.frame(Stimulation, IL10_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("IL10") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in IL4 based on Li et al. 2018
RETNLB <- marker_expression[21, ]
RETNLB$ensembl = NULL
RETNLB$symbol = NULL
RETNLB_new<-as.data.frame(t(RETNLB))
df = data.frame(Stimulation, RETNLB_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("RETNLB") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in IL4 based on Li et al. 2018
ARG1 <- marker_expression[1, ]
ARG1$ensembl = NULL
ARG1$symbol = NULL
ARG1_new<-as.data.frame(t(ARG1))
df = data.frame(Stimulation, ARG1_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("ARG1") +
xlab("Stimulation") + ylab("log2((TPM)+1)")ENTPD1 <- marker_expression[10, ]
ENTPD1$ensembl = NULL
ENTPD1$symbol = NULL
ENTPD1_new<-as.data.frame(t(ENTPD1))
df = data.frame(Stimulation, ENTPD1_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot() +
ggtitle("ENTPD1") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#purinergic receptors increase after ATP stimulation
P2RY4 <- marker_expression[20, ]
P2RY4$ensembl = NULL
P2RY4$symbol = NULL
P2RY4_new<-as.data.frame(t(P2RY4))
df = data.frame(Stimulation, P2RY4_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("P2RY4") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#purinergic receptors increase after ATP stimulation
P2RX7 <- marker_expression[19, ]
P2RX7$ensembl = NULL
P2RX7$symbol = NULL
P2RX7_new<-as.data.frame(t(P2RX7))
df = data.frame(Stimulation, P2RX7_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("P2RX7") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased after ATP stimulation
TMEM163 <- marker_expression[24, ]
TMEM163$ensembl = NULL
TMEM163$symbol = NULL
TMEM163_new<-as.data.frame(t(TMEM163))
df = data.frame(Stimulation, TMEM163_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("TMEM163") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be increased in culture based on Gosselin 2017
MAFB <- marker_expression[15, ]
MAFB$ensembl = NULL
MAFB$symbol = NULL
MAFB_new<-as.data.frame(t(MAFB))
df = data.frame(Stimulation, MAFB_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("MAFB") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be reduced in culture based on review Roy/Frederieke
CX3CR1 <- marker_expression[5, ]
CX3CR1$ensembl = NULL
CX3CR1$symbol = NULL
CX3CR1_new<-as.data.frame(t(CX3CR1))
df = data.frame(Stimulation, CX3CR1_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("CX3CR1") +
xlab("Stimulation") + ylab("log2((TPM)+1)")#expected to be reduced in culture based on review Roy/Frederieke
C3 <- marker_expression[2, ]
C3$ensembl = NULL
C3$symbol = NULL
C3_new<-as.data.frame(t(C3))
df = data.frame(Stimulation, C3_new)
ggplot(data = df, mapping = aes(x = Stimulation, y = V1)) +
geom_boxplot()+
ggtitle("C3") +
xlab("Stimulation") + ylab("log2((TPM)+1)")marker_expression$ensembl = NULL
marker_expression$symbol = NULL
marker_expression = as.matrix(marker_expression)
heatmap(marker_expression)